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Abstract

Modelling and simulating technological materials requires robust predictions of their crystal structure and functional properties. To this end we combine electronic-structure calculations at different levels of coarse-graining with data-driven approaches. Density-functional theory (DFT) as accurate small-scale method is complemented with tight-binding (TB) and analytic bond-order potentials (BOPs) as approximate large-scale methods that preserve the quantum-mechanical nature of the interatomic bonds. The chemical trends identified at the TB/BOP level are used to develop descriptors that chart the experimentally observed structural stability in low-dimensional structure maps. The moments of the electronic density of states at the BOP level are used as descriptors of local atomic environments for machine-learning the results of DFT calculations. In this talk we will review recent applications of these methods to superalloys, high-entropy alloys, intermetallics and steels.